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PRACHI GUPTA

Membro dal giorno 2026

Campionato Argento

1127 punti
AI responsabile per sviluppatori: equità e bias Earned ago 2, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation Earned lug 30, 2026 EDT
Secure Software Delivery Earned lug 30, 2026 EDT
Arcade Base Camp July 2026 Earned lug 30, 2026 EDT
Crea l'infrastruttura con Terraform su Google Cloud Earned lug 29, 2026 EDT
Build a Data Warehouse with BigQuery Earned lug 28, 2026 EDT
Use APIs to Work with Cloud Storage Earned lug 27, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI Earned lug 27, 2026 EDT
Discover and Protect Sensitive Data Across Your Ecosystem Earned lug 27, 2026 EDT

Questo corso introduce i concetti di AI responsabile e i principi dell'AI. Tratta le tecniche per identificare sostanzialmente l'equità e i bias e mitigare i bias nelle pratiche di AI/ML. Illustra metodi e strumenti pratici per implementare le best practice dell'AI responsabile utilizzando gli strumenti open source e i prodotti Google Cloud.

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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production. Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Agent Platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

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Complete the intermediate Secure Software Delivery skill badge to demonstrate your proficiency in proactively integrating security into the software development lifecycle (SDLC) with DevSecOps principles. You'll learn how to utilize Google Kubernetes Engine (GKE) and Cloud Run for secure container image deployment, implement automated vulnerability scanning to proactively identify risks, and streamline application development with Artifact Registry while maintaining a focus on security. Additionally, you'll gain skills in integrating Cloud Build for robust development processes and implementing Admission Control Policies for fine-grained control over your environment.

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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!

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Completa il corso intermedio con badge delle competenze Crea l'infrastruttura con Terraform su Google Cloud per dimostrare le tue competenze nei seguenti ambiti: principi di Infrastructure as Code (IaC) utilizzando Terraform, provisioning e gestione di risorse Google Cloud con configurazioni Terraform, gestione efficace dello stato (locale e remoto) e modularizzazione del codice Terraform per la riusabilità e l'organizzazione.

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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.

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Complete the introductory Use APIs to Work with Cloud Storage skill badge to demonstrate skills in the following: using APIs to work with Cloud Storage resources, including the Cloud Storage API.

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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.

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Complete the intermediate Discover and Protect Sensitive Data Across Your Ecosystem skill badge to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention (DLP) API) to discover, inspect, redact, and de-identify sensitive data across your Google Cloud ecosystem including Cloud Storage files, BigQuery data, and Gen AI model responses.

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